PrepShorts · Study sheet · Class 11 Mathematics · Chapter 14, Probability
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The rule is one line long, which is exactly why it is worth taking apart. It uses two of the three axioms and not the third, it does not need the outcomes to be equally likely, and the standard ten-card illustration is chosen so that naming the complement by a property gets it wrong. All of that is measured here rather than asserted.
The idea
An event and the outcomes it omits cannot both occur, and between them they leave nothing out — so the additivity axiom applies to the pair and the value of the sure event fixes their total at 1. The chapter reaches the result in a single line from two of its three axioms, and what it buys is not a new fact but a choice of route: whenever the omitted outcomes are easier to count or to describe than the event itself, count those instead and subtract. The chapter's own illustration carries a second lesson it does not draw out — the complement is fixed purely by what the event leaves behind, so no property of the event's own members can be relied on to name it, and the chapter's ten-card complement is exactly the case where the obvious property gets the answer wrong.
What you should be able to do
- Prove that an event and its complement have probabilities totalling 1, naming the two axioms used
- Write the complement of a stated event as an explicit list, and check the two sizes total the size of the sample space
- Explain why the complement need not be describable by any single shared property of its members
- Choose, given a question, whether to compute an event or its complement, and justify the choice
- Recognise phrasings that signal a complement, and rewrite them
- Chain the complement with the two-event rule to answer questions about neither of two events occurring
- Identify the one probability that equals its own complement
Words to know
| Term | Definition in one line | First introduced |
|---|---|---|
| complementary event | the event holding exactly the outcomes a given event omits | printed in this chapter, §14.1.3, p. 291, and in the Summary, p. 312 |
| not A | the reading of the complement as a description, which the chapter uses as a section heading | printed in this chapter as part of the heading of §14.2.4, p. 301 |
| mutually exclusive events | events no two of which can be satisfied by one outcome | printed in this chapter from §14.1.4, p. 292; §14.2.4 reaches for it again on p. 302 |
| exhaustive events | events whose union is the whole sample space | printed in this chapter from §14.1.5, p. 293; §14.2.4 reaches for it again on p. 302 |
| sure event | the event holding every outcome, whose value an axiom fixes at 1 | printed in this chapter, §14.1.2, p. 290 |
| equally likely | the hypothesis the chapter announces it will carry from p. 302 onward | printed in this chapter, §14.2.4, p. 302 |
| Demorgan | the rule turning "neither of two" into the complement of "either of two" | printed in this chapter with that spelling, in the solution to Example 7, p. 304 |
| complement trigger | an added name for wordings such as "at least one" that signal the shortcut | an added term; the chapter uses such wordings repeatedly and never comments on the pattern |
| derangement | an arrangement leaving nothing in its own place | an added term; not printed in this chapter, which sets the situation as an exercise without naming it |
Where people slip up
- "The complement of the even numbers is the odd numbers." Only if the event was all the even numbers. The chapter's event holds four of the five evens available, so its complement holds 10 as well as the five odds. Name the complement by exclusion, never by a property.
- "The rule needs the outcomes to be equally likely." It does not. The proof uses the value of the sure event and additivity, and nothing else. The chapter demonstrates it inside an equally-likely example, which makes the dependence look real when it is not.
- "Not A is a different experiment." Same experiment, same outcome list. Only the subset changes.
- "At least one means exactly one." They are different events with different probabilities, and Example 7 computes both — 0.98 for one and 0.11 for the other.
- "Neither happening is found by multiplying the two failures." That would need a multiplication rule, and this chapter has none. Neither independence nor conditional probability is defined anywhere from p. 289 to p. 313 — checked against every page image. The route the chapter uses is the complement of the union.
- "A probability cannot equal its complement." One can, and exactly one does. Example 5's black-card part is it.
- "Subtracting from 1 is a shortcut you take when you are stuck." It is a theorem, and in the envelope question it is the difference between one count and three.
- "The complement of an event of probability 0.02 is 0.98, so the complement of an event of probability 0.13 is 0.13 less than 1." Both are right, but students frequently subtract the wrong quantity when two events are in play. Always name which event is being complemented before subtracting.
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Worked answers: Exercise 14.1 · Exercise 14.2 · Miscellaneous Exercise · this video explains Exercise 14.2 Q2, Exercise 14.2 Q8, Exercise 14.2 Q9, Exercise 14.2 Q16, Miscellaneous Exercise Q1, Miscellaneous Exercise Q5, Miscellaneous Exercise Q6
Transcript2,383 words
The additive axiom is fussy. It only speaks about two events that cannot both occur. For most pairs it has nothing to say at all. But there is one pair it was made for, and every event has one. Take any event, and take everything the experiment can still do instead. Those two share no outcome, because an outcome is either in the event or it is not. And between them they leave nothing out, for the same reason.
That is not an observation about a nice example. On all one thousand and twenty-four events of a ten-outcome list, on all two hundred and fifty-six of an eight-outcome one, and on all sixteen of a four-outcome one, there is not a single exception. Both halves are doing work, and neither implies the other. Two single cards share nothing and cover almost none of the pack. The first seven cards and the last seven cover everything and share four.
Only the pair of an event and what it omits does both at once. Ten cards, numbered one to ten, one drawn. Every card is worth a tenth, and the ten tenths total one. Take the event holding two, four, six and eight. Four cards, each worth a tenth, so the event is worth four tenths. Two fifths. Now write down what it omits. One, three, five, seven, nine, and ten.
Six cards, so six tenths, which is three fifths. Four and six make ten, and two fifths and three fifths make one. Nothing has been proved yet. That is one example, and one example is a coincidence until it is shown not to be. Before the proof, look hard at the six cards that were left. One, three, five, seven, nine. And ten. The ten is even, and it is in there.
The event was never the even numbers. It was four particular even numbers, and there are five available. So a student who names the omitted cards by a property, and says they are the odd ones, is wrong. The odd cards number five, and the omitted cards number six. That answer comes to one half instead of three fifths. It is short by a tenth, and the one card it loses is the ten.
The omitted outcomes are fixed by exclusion. They are whatever is left, and no property of the event's own members can be trusted to name them. How unusual is that? Write down twenty plain descriptions of the ten cards. Even, odd, prime, composite. A perfect square, a perfect cube, a multiple of three, of four, of five. Below five, above five, at most three, at least eight. A single digit, two digits, a factor of ten, a factor of twelve.
A triangular number, a Fibonacci number, and the one card that is neither prime nor composite. Those twenty name twenty different sets of cards. Not one of them names the event we started with. The nearest is even, and it is off by exactly one card, and that card is the ten. Now the sharper count. Of those twenty named sets, only four have an omission that any of the twenty also names.
Sixteen of them leave behind a collection of cards with no name in the list at all. Even the event holding no card is one card short of being nameable. The nearest description to it is two digits, which names the ten alone. Naming is the exception here, not the rule. Now the proof, and it is one line long. Step away from the cards, because the cards are illustration and the proof does not need them.
An event and what it omits cannot both occur. So the additive axiom applies, and their two values add. Between them they hold every outcome, so what they add up to is the value of the sure event. And a second axiom fixes that at one. Therefore the two values total one, and knowing either one hands you the other. Two axioms were used. Additivity across a pair that cannot both occur, and the value of the sure event.
The third axiom, the one saying no value is negative, was not used. Neither was the assumption that the outcomes are equally likely. That is easy to say and easy to doubt, so it is worth measuring. Here is a table on the ten cards that carries a negative entry. One card is worth minus a tenth, and the other nine are worth eleven ninetieths each. It totals one, and it is not admissible, because a probability is never negative.
Run the rule on it anyway. It holds on every one of the one thousand and twenty-four events. So non-negativity really was not what the proof leaned on. Now a table that is perfectly non-negative and totals nine tenths instead of one. The rule fails on every one of the thousand and twenty-four. That is the axiom that was load-bearing. And a table giving the ten cards ten different weights, all legitimate, holds the rule everywhere.
Equal likelihood was never needed. One control, to show the test can fail. Give every event the square of its size over the square of ten. That function is never negative, it gives the sure event one, and it is not additive. The rule fails on one thousand and twenty-two of the thousand and twenty-four events. The two it survives are the event holding nothing and the event holding everything, which is to say the two where there was nothing to add.
So what has been bought? Not a new fact. Every value the rule produces could have been had by totalling the omitted outcomes directly. Those two routes agree on every event of the ten cards, under an even table and under an uneven one. They agree on every event of three tossed coins, and on every event of a four-outcome list weighted a half, a quarter, an eighth and an eighth.
What has been bought is a choice of route. Whenever the omitted outcomes are easier to count, or easier to describe, count those instead and subtract. And notice which of the two things in this video actually needs the equally likely hypothesis. It is not the rule. It is the habit of reading a probability off a count. Size over ten agrees with the even table on all one thousand and twenty-four events, and comes apart from the uneven table on nine hundred and seventy-six of them.
It agrees on only forty-eight. A deck of fifty-two cards, one drawn. Four of them are aces, so an ace is four fifty-seconds, which is one thirteenth. What is not an ace? Subtract, and it is twelve thirteenths. Or total the forty-eight cards that are not aces, and it is twelve thirteenths. The two routes agree, which is the plainest evidence that this is a theorem and not a trick.
But look at the effort. One route counts four cards, the other counts forty-eight, which is twelve times as many. Thirteen cards are diamonds, so a diamond is a quarter and not a diamond is three quarters. Nine discs, four red, three blue, two yellow. Blue is three ninths, which is a third. Not blue is two thirds by subtracting, and two thirds by counting the six discs that are not blue.
Twenty-six cards are black, so a black card is a half. And a card that is not black is also a half. Students read that as an error, and it is not. Of the hundred and one values in hundredths, exactly one equals what remains after it, and it is a half. A number is what is left over from one only at the halfway point. On the ten cards there are two hundred and fifty-two events out of the thousand and twenty-four worth exactly what they omit.
Every single one of them holds five cards. But that is a fact about the even table and not about the number five. Put the uneven weights back on the same ten cards, and not one of the thousand and twenty-four events is worth what it omits. The half is a value, not a size. Now the phrase that always means take the omitted outcomes. At least one. Three coins are tossed, eight outcomes, an eighth each.
How likely is at least one head? Counting directly means one head, or two heads, or three heads. Counting what it omits means no head, which is one outcome, worth an eighth. So at least one head is seven eighths, and the seven outcomes are there to check. At most two tails is the same shape of question. It omits three tails, one outcome, so it is seven eighths as well.
One warning while we are here. At least one head and exactly one head are different events. At least one holds seven outcomes and exactly one holds three, and their values are not equal. Two candidates sit an entrance test. Ana qualifies with probability nought point nought five, Ben nought point one, and both of them nought point nought two. At least one qualifying is the two-event rule, and it is nought point one three.
Now neither of them qualifies. That is what at least one omits, so it is one less nought point one three, which is nought point eight seven. And at least one of them fails. That is what both qualifying omits, so it is one less nought point nought two, which is nought point nine eight. Two complements in one question, taken against two different events, and mixing them up is the commonest mistake here.
The step from neither to the complement of either needs a rule about sets. Neither of two events is the complement of at least one of them. On all four hundred and ninety-six pairs of events on a five-outcome list that holds with no exceptions, and so does its partner. Swapping the two operations round breaks it on every one of the four hundred and ninety-six. Four more, quickly, because the pattern is the whole point.
An event worth two elevenths omits nine elevenths. Two events with a union of five eighths leave neither of them at three eighths. A student on at least one activity is nineteen thirtieths, so a student on neither is eleven thirtieths. And if not both is nought point two five, then both is nought point seven five, which is not nothing, so the two can happen together. Every one of those was reached by totalling the omitted outcomes over their own members, not by subtracting.
You can tell, because the same routine asked about a table totalling nine tenths gives thirty-six hundredths and fifty-four hundredths. Those come to nine tenths, which is exactly what a subtraction could not have produced. Three letters go into three envelopes at random, one each. What is the chance at least one letter reaches the right envelope? There are six arrangements, so write them all out. Sort them by how many letters land right.
Two arrangements put nothing in its own place. Three put exactly one. None put exactly two. And one puts all three. That none is not an accident. If every letter but one is right, the last one has nowhere else to go, so it is right too. For every number of letters from two up to seven, the count of arrangements with exactly one wrong is nought. So nothing in its own place is two arrangements out of six, and at least one right is four out of six, which is two thirds.
Count it directly and you have two cases to add. Count what it omits and you have one. The arrangements with nothing in place go nought, one, two, nine, forty-four, two hundred and sixty-five, one thousand eight hundred and fifty-four. The direct route gets worse quickly, and the other one never does. A hundred students, split into groups of forty and sixty, and two of them are picked. There are four thousand nine hundred and fifty pairs in all.
Pairs from inside the smaller group number seven hundred and eighty. Pairs from inside the larger number one thousand seven hundred and seventy. Together, two thousand five hundred and fifty, so both from the same group is seventeen thirty-thirds. The other question, one from each group, should never be counted directly. It is what the first omits, so it is sixteen thirty-thirds. And it checks out: two thousand four hundred mixed pairs, and the two counts account for every pair there is.
Three last questions, each of which looks like something else. Sixty marbles, ten red, twenty blue, thirty green, and five are drawn. At least one green. Directly, that is five separate cases, one green, or two, or three, or four, or five, and every one of the five terms matters. Drop any single one and the answer changes. What it omits is one case. All five drawn from the thirty that are not green, which is a hundred and seventeen over four thousand four hundred and eighty-four.
So at least one green is four thousand three hundred and sixty-seven over four thousand four hundred and eighty-four. Ten thousand lottery tickets and ten prizes. One ticket wins with probability one in a thousand, so it does not win with probability nine hundred and ninety-nine in a thousand. And a die whose faces carry one, one, two, two, two and three. One face shows a three, so not a three is five sixths.
In each of these you were asked for the bigger side, and the arithmetic counted the smaller one. One last thing, and it is the thing the ten cards were really showing. What an event omits is not a property of the event. It is a property of the event and the experiment together. The same four cards, two, four, six and eight, omit six cards inside a pack of ten.
Inside a pack of twelve they omit eight, and two of those eight are even. The event did not change at all. The experiment did. So do not name what is left by looking at what you took. Name it by looking at what is there. Then subtract, and let the axiom do the rest.
Where this fits
Taken from the notes each video was made from, not from the reading order — these are the ideas this one rests on and the ones that later rest on it.
Builds on
- Three conditions on a function, in place of a recipe for countingClass 11 · Ch 14, Probability
- Adding two probabilities double-counts the overlap, so the overlap comes back offClass 11 · Ch 14, Probability
- "Or", "and" and "not" are the three set operations under new namesClass 11 · Ch 14, Probability
- Events that cannot both happen, and events that between them mustClass 11 · Ch 14, Probability
Either side of this one
- A relation as a subset of a product set, and the two extreme casesClass 12 · Ch 1, Relations and Functions